T.K. designed and performed most of the experiments, analyzed the data, and wrote the article together with A.J.M.; N.B. developed the piecewise linear regression model, performed measurements on almond trees, and revised the article; M.I.H helped with measurements of water potential and collected leaf pressure volume curves on walnuts, and revised the article; F.D. helped with measurement of water potential and leaf gas exchange on walnuts; M.K.B. acquired plant material, obtained funding for grapevine research, designed the grapevine experiment, and revised the article; S.G. performed measurement of water potential and leaf gas exchange on grapevines; D.A.K. obtained funding for walnut research, acquired the plant material, helped in experimental design, and revised the article; A.J.M. obtained funding, helped in experimental design and wrote the article together with T.K.

Ralstonia cause wilt diseases by colonizing xylem vessels and disrupting water transport. The dogma is that bacterial biomass clogs vessels and reduces the flow of xylem sap due to Ralstonia abundance. However, the physiological mechanism of xylem disruption during bacterial wilt is untested. Using a tomato and Ralstonia pseudosolanacearum GMI1000 model, we visualized and quantified spatiotemporal dynamics of xylem disruption during bacterial wilt. First, we measured stomatal conductance of leaflets on mock-inoculated and wilt-symptomatic plants. Wilted leaflets had reduced stomatal conductance, as did turgid leaflets on the same petiole as wilted leaflets. Next, we used X-ray microcomputed tomography (X-ray microCT) and light microscopy to differentiate between mechanisms of xylem disruption: blockage by bacterial biomass, blockage by vascular tyloses, or sap displacement by gas embolisms. We imaged intact plant stems to quantify embolized vessels. Embolized vessels were rare, but infected plants with low bacterial populations had a non-significant trend of more vessel embolisms. To test that vessels are clogged during bacterial wilt, we imaged excised stems after brief dehydration. Most vessels in mock-infected plants emptied their contents after excision, but non-conductive clogged vessels were abundant in infected plants by 2 days post infection. At wilt onset when bacterial populations exceeded 5x108 cfu/g stem tissue, approximately half of the vessels were clogged with electron-dense bacterial biomass. We found no evidence of tyloses in X-ray microCT reconstructions or from light microscopy of preserved stems. Therefore, bacterial blockage of vessels appears to be the principal cause of xylem disruption during Ralstonia wilt.

Plant pathogenic Ralstonia cause wilt diseases by colonizing xylem vessels and disrupting water transport. Due to the abundance of Ralstonia cells in vessels, the dogma is that bacterial biomass clogs vessels and reduces the flow of xylem sap. However, the physiological mechanism of xylem disruption during bacterial wilt disease is untested. Using a tomato and Ralstonia pseudosolanacearum GMI1000 model, we visualized and quantified the spatiotemporal dynamics of xylem disruption during bacterial wilt disease. First, we measured stomatal conductance of leaflets on mock-inoculated and wilt-symptomatic plants. Wilted leaflets had reduced stomatal conductance, as did turgid leaflets located on the same petiole as wilted leaflets. Next, we used X-ray microcomputed tomography (X-ray microCT) and light microscopy to differentiate between mechanisms of xylem disruption: blockage by bacterial biomass, blockage by vascular tyloses, or sap displacement by gas embolisms. We imaged stems on plants with intact roots and leaves to quantify embolized vessels. Embolized vessels were rare, but there was a slight trend of increased vessel embolisms in infected plants with low bacterial population sizes. To test the hypothesis that vessels are clogged during bacterial wilt, we imaged excised stems after allowing the sap to evaporate during a brief dehydration. Most xylem vessels in mock-infected plants emptied their contents after excision, but non-conductive clogged vessels were abundant in infected plants by 2 days post infection. At wilt onset when bacterial populations exceeded 5x108 cfu/g stem tissue, approximately half of the xylem vessels were clogged with electron-dense bacterial biomass. We found no evidence of tyloses in the X-ray microCT reconstructions or light microscopy on the preserved stems. Bacterial blockage of vessels appears to be the principal cause of vascular disruption during Ralstonia wilt.

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

Similar to other cropping systems, few walnut cultivars are used as scion in commercial production. Germplasm collections can be used to diversify cultivar options and hold potential for improving crop productivity, disease resistance and stress tolerance. In this study, we explored the anatomical and biochemical bases of photosynthetic capacity and response to water stress in 11 Juglans regia accessions in the U.S. department of agriculture, agricultural research service (USDA-ARS) National Clonal Germplasm. Net assimilation rate (A n ) differed significantly among accessions and was greater in lower latitudes coincident with higher stomatal and mesophyll conductances, leaf thickness, mesophyll porosity, gas-phase diffusion, leaf nitrogen and lower leaf mass and stomatal density. High CO 2 -saturated assimilation rates led to increases in A n under diffusional and biochemical limitations. Greater A n was found in lower-latitude accessions native to climates with more frost-free days, greater precipitation seasonality and lower temperature seasonality. As expected, water stress consistently impaired photosynthesis with the highest % reductions in lower-latitude accessions (A3, A5 and A9), which had the highest A n under wellwatered conditions. However, A n for A3 and A5 remained among the highest under dehydration. J. regia accessions, which have leaf structural traits and biochemistry that enhance photosynthesis, could be used as commercial scions or breeding parents to enhance productivity.